How procedural memory can cut the cost and complexity of AI agents
Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now A new technique from Zhejiang University and Alibaba Group gives large language model (LLM) agents a dynamic memory, making them more efficient and effective at complex tasks. The technique, called Memp, provides agents with a “procedural memory” that is continuously updated as they gain experience, much like how humans learn from practice. Memp creates a lifelong learning framework where agents don’t have to start from scratch for every new task. Instead, they become progressively better and more efficient as they encounter new situations in real-world environments, a key requirement for reliable enterprise automation….
